R package gamlss used inside foreach() fails to find an object - r

Question

I'm trying to get leave-one-out predicted values. Please help me with this "can't find object" issue. I have searched for similar issues, but haven't managed to figure it out. This is on Windows 10.
Thanks in advance
library('gamlss')
library('foreach')
library('doParallel')
registerDoParallel(cores = 4)
# Generate data
set.seed(314)
sample.size <- 30
input.processed.cut <- data.frame(TP = round(runif(sample.size) * 100),
FP = round(runif(sample.size) * 100),
x = runif(sample.size))
# Fit Beta-binomial
model3 <- gamlss(formula = cbind(TP, FP) ~ x,
family = BB,
data = input.processed.cut)
# Get the leave-one-out values
loo_predict.mu <- function(model.obj, input.data) {
yhat <- foreach(i = 1 : nrow(input.data), .packages="gamlss", .combine = rbind) %dopar% {
updated.model.obj <- update(model.obj, data = input.data[-i, ])
predict(updated.model.obj, what = "mu", newdata = input.data[i,], type = "response")
}
return(data.frame(result = yhat[, 1], row.names = NULL))
}
par.run <- loo_predict.mu(model3, input.processed.cut)
# Error in { : task 1 failed - "object 'input.data' not found"
> version
_
platform x86_64-w64-mingw32
arch x86_64
os mingw32
system x86_64, mingw32
status
major 3
minor 4.3
year 2017
month 11
day 30
svn rev 73796
language R
version.string R version 3.4.3 (2017-11-30)
nickname Kite-Eating Tree

Answer 1

I got a response from gamlss team and verified that their solution works. The only thing to change was to provide "data" along with "newdata" to predict().
loo_predict.mu <- function(model.obj, input.data) {
yhat <- foreach(i = 1 : nrow(input.data), .packages="gamlss", .combine = rbind) %dopar% {
updated.model.obj <- update(model.obj, data = input.data[-i, ])
predict(updated.model.obj, what = "mu", data = input.data[-i, ],
newdata = input.data[i,], type = "response")
}
return(data.frame(result = yhat[, 1], row.names = NULL))
}